Journal of the Knowledge Economy最新文献

This study addresses the critical gap in understanding the risks associated with digital transformation, particularly focusing on their impact on business innovation and growth within Industry 4.0. While the transformative potential of digital technologies is well-documented, the inherent challenges remain underexplored. This research introduces an innovative decision-support model designed to evaluate and prioritize risks unique to digital transformation in the industrial sector. Utilizing Pythagorean fuzzy sets (PFSs) and multicriteria decision-making (MCDM) techniques, the model systematically assesses and ranks risks to enhance informed decision-making processes. An extensive case study reveals that key risks include a lack of commitment from top management and unstable market environments, which significantly jeopardize the digital transformation journey. The study’s findings underscore the importance of a strategic approach in mitigating these risks, facilitating a smoother transition to the digital economy. The proposed model offers actionable insights for organizations to optimize their digital transformation strategies by integrating advanced analytics and machine learning. This research contributes to the knowledge economy by providing a robust framework for managing the complexities of digital transformation, promoting sustainable innovation, and enhancing overall business performance. The study’s strengths are further reinforced through sensitivity and comparison analyses, highlighting the resilience and practical applicability of the decision-support model. These insights are invaluable for policymakers, industry leaders, and scholars focused on leveraging technology to drive economic growth and societal progress in the era of Industry 4.0.

Economic policies often play a substantial role in shaping environmental quality worldwide. In light of this, this research analyzes the impact of economic policy, particularly “fiscal and monetary policy (FMP)” on CO₂ discharges and ecological footprint (EF) in South Asian (SA) countries based on the “environmental Kuznets curve (EKC)” framework, controlling disaggregated energy consumption. It employs a “pooled mean group (PMG)” estimate and a “Dumitrescu-Hurlin causality check” using panel data for the years 1990–2021. The PMG estimate confirms a persistent connection between variables of interest. The research backs up the EKC hypothesis for the SA nations, showing a link between reduced ecological footprint and CO₂ discharges, increased usage of renewable energy, and FMP. Nonrenewable energy use increases ecological footprint and carbon emissions, whereas per capita GDP increases pollution, and GDP² per capita lowers pollution. The D-H causality testing confirms the reliability of PMG results by revealing several unidirectional and bidirectional causal relationships. Based on our research, we conclude that efficient fiscal and monetary instruments are one of the most essential tools for reducing SA countries’ ecological footprints and CO₂ emissions.

I examine and compare patent licensing by fixed fee and unit royalty under Cournot competition. I consider licensing by an incumbent patent holder to one or two other competing firms that can obtain a patented technological improvement through technology transfer or imitation. Assuming that imitation is perfect, certain, instantaneous, and non-infringing, I analyze the effects of licensing on market structure, firms’ individual profits, and consumer surplus. This provides a theoretical framework that explains when technology licensing is superior to imitation for both firms and consumers, what is the optimal licensing choice for firms, and how imitation affects firms’ licensing behavior and competition in a highly concentrated industry. In particular, I show that licensing through a unit royalty is preferable to licensing through a fixed fee for a patent holder, while licensing through a fixed fee is at least as beneficial as licensing through a unit royalty for consumers. Moreover, the patent holder can use licensing to prevent imitation, but cannot use it selectively to affect competition, at least before the patent expires and when one of the competing firms can imitate. I contribute to the literature that considers the patent holder as a producer by showing how technology licensing can affect competition and improve consumer surplus in oligopolistic industries. This is important for policy makers to identify when technology licensing is used strategically to transfer surplus from consumers to producers.

The aim of this paper is to highlight the importance and resilience of small and medium-sized enterprises (SMEs) in the Greek economy through a mixed method of primary and secondary quantitative data analysis. In tandem, the critical importance of adopting the appropriate policy measures for SMEs is discussed as a fundamental precondition for sustainable development and economic democracy. In this context, aspects and dimensions of the business environment for the operation and growth of SMEs in Greece are presented. The paper analyses several policy aspects that accompany the dominant economic policy choices during the last decades. In this light, it seems over time that in terms of economic policy, SMEs, despite their significant contribution to the entrepreneurship ecosystem, are mainly approached either as a growth obstacle or a structural weakness of the Greek economy. However, given the socio-economic importance of SMEs, the shift towards a new knowledge-based growth model of the Greek economy needs to consider their significant historical, economic and social role. In conclusion, the need to formulate targeted policy measures to support SMEs is discussed, focusing mainly on cooperation, financing, digital transformation and green transition.

The organization uses traditional models, but a circular economy has emerged as an alternative to achieve the environmental sustainability goals. In the struggle against the depletion of global resources and environmental damage, frameworks for a circular economy have arisen as a significant issue for discussion and intervention. Scopus provides the data used to execute topic modeling in this research. For information modeling, we employ Latent Dirichlet Allocation (LDA) to extract the study topics in environmental sustainability from the corpus of 4488 research articles published between 2005 and 2023. Predicted research subjects for the circular economy, which requires further study in the future, include 2, 5, and 10 and are based on a bag of words identified by clustering techniques. The academic community needs more investigation of these tendencies for their long-term viability. The circular economy aims to reduce or eliminate waste. It's a system that creates lots of money for the economy yet doesn't harm the environment too much. Of the 17 research trends identified by the applied LDA techniques, 5 are the most explored by the researchers, while 4 have received the least attention.

This paper investigates the multidimensional effects of both formal and informal gender norms on female labor force participation in Sub-Saharan Africa. The analysis includes a sample of 42 Sub-Saharan African nations between 2009 and 2019. Using a panel quantile regression model, the findings reveal that gender stereotypes significantly limit young women’s employment opportunities, regardless of whether they reside in rural or urban areas. This effect is amplified in rural areas as fertility rates increase. Discrimination related to physical integrity, access to resources, male preference, civil liberties, and bargaining power further impacts women’s participation in the labor market. In light of these findings, Sub-Saharan African countries must develop programs for women and girls or enact laws to combat discriminatory practices. Examples of such initiatives include efforts to reduce gender-based norms, like the Oxfam We-Care initiative, and promoting education for women, which has been shown to positively impact female labor supply.

This systematic review critically examines the technological, organizational, and environmental (TOE) factors influencing e-commerce adoption among small and medium-sized enterprises (SMEs) over the past decade. By dissecting the distinct roles of these TOE factors, the review identifies both the facilitators and inhibitors affecting SMEs as they navigate the complexities of e-commerce integration. The analysis reveals that while technological innovations and digital readiness significantly drive adoption, SMEs face persistent challenges related to resource limitations, cybersecurity concerns, and rapid technological change. Organizational readiness, highlighted by change management and strategic alignment, emerges as a critical determinant, whereas the environmental context, including market trends and regulatory policies, shapes the e-commerce landscape within which SMEs operate. This review emphasizes the need for a nuanced understanding of these multidimensional factors and recommends targeted interventions to alleviate barriers. Suggestions for future research include longitudinal studies to track the evolution of e-commerce adoption strategies, the impact of emerging technologies on SMEs’ competitive advantage, and the role of government policy in fostering a supportive ecosystem for digital transformation.

The purpose of this work is to analyze the effectiveness of management of the agro-industrial complex based on the introduction of digital and intelligent technologies that contribute to reducing the technological gap relative to the developed countries of the world, as well as stimulating the economic growth in Kazakhstan. The following methods were used in the study: information-logical, analysis and synthesis, systematization, economic modeling, and monitoring. As a result of the research, the difficulties, objective factors, and trends that determine the processes of agriculture in Kazakhstan were analyzed. It is given an economic assessment of the existing agro-industrial complex; it is established that an increase in the level of agricultural production depends on the need for new technical support and digital modernization. Based on the results of the SWOT analysis, it has been found that the environmental and economic conditions for the development of precision farming in the North Kazakhstan region require the government support that contributes to the development of new infrastructure. Practical solutions for digitalization processes of agro-industrial complex based on the high potential will lead to the creation of environmentally sustainable programmable farming and productive animal husbandry based on the advanced geospatial technologies, robotics, and artificial intelligence in general.

Available literature shows that the economic structure of countries can influence trade, foreign direct investment (FDI) inflow, environmental degradation, and economic growth across nations. However, this literature is scarce in Africa. Besides, economic governance institutions are important factors that may affect growth. Hence, this paper investigates how economic governance institutions are moderating the effect of economic complexity on trade, FDI inflow, environmental degradation, and economic growth in Africa from 2000 to 2020. Employing the system GMM and marginal effect techniques, our results show that: (i) economic governance institutions provide important channels through which economic complexity drives trade, FDI inflow, and economic growth in Africa; and (ii) governance institutions in Africa moderate the effect of economic complexity on the environment by stimulating economic activities that lead to higher carbon dioxide emissions as a byproduct of growth. Overall, we find evidence that improved governance institutions in Africa are capable of intensifying trade, attracting more FDI, and spurring economic growth. The study made some insightful policy recommendations based on these findings.

This study aims to explore the spatiotemporal convergence effects of industrial green technological innovation efficiency and its influencing factors to facilitate the transformation of the Yangtze River Economic Belt from a traditional high-pollution, high-emission, and high-energy-consumption industrial model to a green, efficient, and sustainable economic development model. By applying the Super-SBM model, the absolute beta convergence model, the conditional beta convergence model, and the spatial dynamic Durbin model, this study reveals the dynamic changes in industrial green technological innovation efficiency and its influencing factors in the Yangtze River Economic Belt. The research findings are as follows: (1) Regions with lower industrial green technological innovation efficiency can rapidly improve by learning from more efficient regions, demonstrating a significant “catch-up” effect. The upstream and downstream areas exhibit specific spatial dependencies, while the midstream area does not pass the significance level test. (2) The conditional convergence rate is significantly higher than the absolute convergence rate, indicating the presence of spatial conditional convergence in industrial green technological innovation efficiency among different regions. (3) This study further analyzes the impact mechanisms of six factors—enterprise size, industry-university-research cooperation, enterprise R&D level, environmental regulation, energy consumption structure, and foreign direct investment—on industrial green technological innovation efficiency. The results show that these factors have significant differences in their effects. Finally, this study proposes strategies to optimize green technological innovation efficiency, aiming to provide a reference for the Yangtze River Economic Belt and other regions worldwide to achieve high-quality development with green and low-carbon growth.